Collaborative Research: A Pilot Study of Simultaneous Parameter and State Estimation in Coupled Ocean-Atmosphere General Circulation Models Using the Ensemble Kalman Filter

合作研究：使用集合卡尔曼滤波器同时估计海洋-大气环流耦合模型参数和状态的初步研究

• 批准号: 0968383
• 负责人: Zhengyu Liu
• 金额: $ 50.99万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0968383&HistoricalAwards=false
• 关键词: Collaborative; Research; Pilot; Study; Simultaneous

Ocean Atmosphere General Circulation Models (OAGCM) exhibit significant model biases, e.g., the tropical bias in the Intertropical Convergence Zone cold tongue complex. A significant part of such biases is due to uncertainties in the model parameters. Thus far, however, parameter tuning in OAGCMs remains rudimentary. This collaborative project will develop a novel strategy for systematic parameter optimization in OAGCMs, using an ensemble based data assimilation strategy, focusing on the outstanding tropical bias problem. Building on an existing coupled data assimilation system, an adaptive coupled ensemble Kalman Filter system (AcEnKF) for a simultaneous estimation of model parameter and state, will be developed. Different assimilation techniques to search for an effective method of parameter optimization in OAGCMs will be studied, as also coupled dynamics relevant to parameter optimization in the tropical climate system for both the climatology and climate variability. The work is expected to give the first comprehensive evaluation of the ensemble based strategy for parameter optimization in OAGCMs. The study will also shed light on the mechanism of the coupled dynamics of the tropical climate system and its sensitivity to model parameters. In spite of potential difficulties, this pilot study represents a significant step forward in the improvement of OAGCMs. This activity has significant broader impacts: it will lay a foundation for a systematic improvement of OAGCMs and, more generally, future coupled earth system models.

海洋大气环流模式（OAGCM）表现出明显的模式偏倚，如热带辐合带冷舌复合体的热带偏倚。这种偏差的很大一部分是由于模型参数的不确定性。然而，到目前为止，oagcm中的参数调优仍然处于初级阶段。该合作项目将开发一种新的OAGCMs系统参数优化策略，使用基于集成的数据同化策略，重点关注突出的热带偏置问题。在现有耦合数据同化系统的基础上，开发了一种用于同时估计模型参数和状态的自适应耦合集成卡尔曼滤波系统（AcEnKF）。本文将研究不同的同化技术在OAGCMs中寻找有效的参数优化方法，以及与热带气候系统的气候学和气候变率参数优化相关的耦合动力学。这项工作有望首次对基于集成的oagcm参数优化策略进行全面评估。该研究还将揭示热带气候系统耦合动力学的机制及其对模式参数的敏感性。尽管存在潜在的困难，但这项试点研究代表着在改进oagcm方面迈出了重要的一步。这一活动具有重大而广泛的影响：它将为系统地改进oagcm以及更广泛地改进未来耦合地球系统模式奠定基础。